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import streamlit as st |
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import replicate |
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import os |
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from transformers import AutoTokenizer |
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st.set_page_config(page_title="Snowflake Arctic") |
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def main(): |
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"""Execution starts here.""" |
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get_replicate_api_token() |
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display_sidebar_ui() |
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init_chat_history() |
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display_chat_messages() |
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get_and_process_prompt() |
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def get_replicate_api_token(): |
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os.environ['REPLICATE_API_TOKEN'] = st.secrets['REPLICATE_API_TOKEN'] |
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def display_sidebar_ui(): |
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with st.sidebar: |
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st.title('Snowflake Arctic') |
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st.subheader("Adjust model parameters") |
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st.slider('temperature', min_value=0.01, max_value=5.0, value=0.3, |
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step=0.01, key="temperature") |
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st.slider('top_p', min_value=0.01, max_value=1.0, value=0.9, step=0.01, |
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key="top_p") |
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st.button('Clear chat history', on_click=clear_chat_history) |
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st.sidebar.caption('Build your own app powered by Arctic and [enter to win](https://arctic-streamlit-hackathon.devpost.com/) $10k in prizes.') |
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st.subheader("About") |
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st.caption('Built by [Snowflake](https://snowflake.com/) to demonstrate [Snowflake Arctic](https://www.snowflake.com/blog/arctic-open-and-efficient-foundation-language-models-snowflake). App hosted on [Streamlit Community Cloud](https://streamlit.io/cloud). Model hosted by [Replicate](https://replicate.com/snowflake/snowflake-arctic-instruct).') |
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def clear_chat_history(): |
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st.session_state.messages = [{"role": "assistant", "content": "Hi. I'm Arctic, a new, efficient, intelligent, and truly open language model created by Snowflake AI Research. Ask me anything."}] |
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st.session_state.chat_aborted = False |
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def init_chat_history(): |
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"""Create a st.session_state.messages list to store chat messages""" |
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if "messages" not in st.session_state: |
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clear_chat_history() |
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check_safety() |
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def display_chat_messages(): |
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icons = {"assistant": "./Snowflake_Logomark_blue.svg", "user": "⛷️"} |
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for message in st.session_state.messages: |
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with st.chat_message(message["role"], avatar=icons[message["role"]]): |
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st.write(message["content"]) |
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@st.cache_resource(show_spinner=False) |
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def get_tokenizer(): |
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"""Get a tokenizer to make sure we're not sending too much text |
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text to the Model. Eventually we will replace this with ArcticTokenizer |
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""" |
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return AutoTokenizer.from_pretrained("huggyllama/llama-7b") |
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@st.cache_resource(show_spinner=False) |
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def get_llamaguard_deployment(): |
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return replicate.deployments.get("snowflake/llamaguard") |
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def check_safety(disable=False) -> bool: |
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if disable: |
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return True |
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deployment = get_llamaguard_deployment() |
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conversation_history = st.session_state.messages |
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prediction = deployment.predictions.create( |
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input = { "prompt": f"[INST] Task: Check if there is unsafe content in 'Agent' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\nO1: Violence and Hate.\nShould not\n- Help people plan or engage in violence.\n- Encourage people to engage in violence.\n- Express hateful, derogatory, or demeaning sentiments against people based on sensitive personal characteristics like their race, color, religion, national origin, sexual orientation, gender, gender identity, or disability.\n- Encourage discrimination against people based on those characteristics and should not use slurs or create insults based on those characteristics.\nCan\n- Provide information on violence and discrimination.\n- Discuss the topics of hate and violence, and can discuss historical events involving violence.\nO2: Sexual Content.\nShould not\n- Engage in sexually explicit (i.e., erotic) conversations and should not encourage people to engage in sexual activities.\nCan\n- Discuss topics related to sexuality and sexual education.\n- Provide general information regarding sexual activities.\n- Provide guidance on topics related to sexual health.\nO3: Criminal Planning.\nShould not\n- Help people plan or engage in criminal activities like theft, kidnapping, or financial crimes, especially when the person indicates that they may act on the information provided to them.\n- Encourage people to engage in criminal activities or condone criminal behavior.\nCan\n- Help people understand how crimes are committed, provided that the response is not so detailed that it could be used to provide a roadmap for future crimes.\n- Help people understand how systems work that are used to prevent crimes, provided those descriptions do not provide detailed information on how to defeat those systems.\nO4: Guns and Illegal Weapons.\nShould not\n- Assist in the planning or execution of firearm or illegal weapons crimes, especially when the person indicates that they may act on the information provided to them.\n- Encourage people to engage in firearm or illegal weapons crimes or condone such behavior.\nCan\n- Discuss firearms and the arguments for and against firearm ownership.\nO5: Regulated or Controlled Substances.\nShould not\n- Encourage or assist people in the trafficking, consumption, or use of regulated or controlled substances, including but not limited to illegal drugs, tobacco, alcohol, and cannabis.\n- Assist or encourage people to create such substances when it is illegal to do so.\nCan\n- Discuss the use of regulated or controlled substances, and can provide general information on those substances (ex: what their chemical composition is and what their effects are).\n- Provide information on how those substances are manufactured, provided that the information is not so detailed as to provide step-by-step instructions for their creation.\nO6: Self-Harm.\nShould not\n- Encourage people to harm themselves.\n- Romanticize or condone self-harm or suicide.\n- Provide information regarding the methods of suicide or self-harm.\n- Provide any information or advice, other than information regarding appropriate health resources, to people who express or imply that they wish to harm themselves.\nCan\n- Provide general information regarding self-harm and suicide (ex: statistics, the mental health challenges faced by those who take these actions).\nShould\n- Provide information regarding appropriate health resources to people who imply or express the desire to harm themselves.\n<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\n{conversation_history}\n\n<END CONVERSATION>\n\nProvide your safety assessment for Agent in the above conversation:\n- First line must read 'safe' or 'unsafe'.\n- If unsafe, a second line must include a comma-separated list of violated categories. [/INST]" } |
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) |
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prediction.wait() |
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output = prediction.output |
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if output is not None and "unsafe" in output: |
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return False |
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else: |
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return True |
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def get_num_tokens(prompt): |
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"""Get the number of tokens in a given prompt""" |
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tokenizer = get_tokenizer() |
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tokens = tokenizer.tokenize(prompt) |
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return len(tokens) |
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def abort_chat(error_message: str): |
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"""Display an error message requiring the chat to be cleared. |
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Forces a rerun of the app.""" |
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assert error_message, "Error message must be provided." |
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error_message = f":red[{error_message}]" |
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if st.session_state.messages[-1]["role"] != "assistant": |
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st.session_state.messages.append({"role": "assistant", "content": error_message}) |
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else: |
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st.session_state.messages[-1]["content"] = error_message |
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st.session_state.chat_aborted = True |
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st.rerun() |
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def get_and_process_prompt(): |
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"""Get the user prompt and process it""" |
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if st.session_state.messages[-1]["role"] != "assistant": |
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with st.chat_message("assistant", avatar="./Snowflake_Logomark_blue.svg"): |
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response = generate_arctic_response() |
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st.write_stream(response) |
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if st.session_state.chat_aborted: |
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st.button('Reset chat', on_click=clear_chat_history, key="clear_chat_history") |
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st.chat_input(disabled=True) |
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elif prompt := st.chat_input(): |
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st.session_state.messages.append({"role": "user", "content": prompt}) |
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st.rerun() |
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def generate_arctic_response(): |
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"""String generator for the Snowflake Arctic response.""" |
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prompt = [] |
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for dict_message in st.session_state.messages: |
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if dict_message["role"] == "user": |
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prompt.append("<|im_start|>user\n" + dict_message["content"] + "<|im_end|>") |
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else: |
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prompt.append("<|im_start|>assistant\n" + dict_message["content"] + "<|im_end|>") |
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prompt.append("<|im_start|>assistant") |
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prompt.append("") |
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prompt_str = "\n".join(prompt) |
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num_tokens = get_num_tokens(prompt_str) |
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max_tokens = 1500 |
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if num_tokens >= max_tokens: |
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abort_chat(f"Conversation length too long. Please keep it under {max_tokens} tokens.") |
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st.session_state.messages.append({"role": "assistant", "content": ""}) |
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for event_index, event in enumerate(replicate.stream("snowflake/snowflake-arctic-instruct", |
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input={"prompt": prompt_str, |
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"prompt_template": r"{prompt}", |
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"temperature": st.session_state.temperature, |
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"top_p": st.session_state.top_p, |
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})): |
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if (event_index + 0) % 50 == 0: |
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if not check_safety(): |
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abort_chat("I cannot answer this question.") |
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st.session_state.messages[-1]["content"] += str(event) |
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yield str(event) |
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if not check_safety(): |
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abort_chat("I cannot answer this question.") |
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if __name__ == "__main__": |
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main() |
